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BF ct-monitor

CT Monitor — Crypto Intelligence Analyst. Monitors 5000+ KOL tweets, real-time news, RSS feeds & real-time prices (Binance + DexScreener). Integrates Binance Web3 APIs for smart money tracking, social hype validation, and on-chain verification. Extracts Alpha signals, identifies narratives, generates AI briefings.

ClawHub Agent Skills author: tizerluo v3.3.18 3 files body ≈ 16 943 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 37/100 · Will not run — References files that are not bundled: url

AnalyzerTelegramInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
98
Quality 40%
54
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 2

✓ No critical or high findings

Medium and low: 2
  • low Exfiltration net-credential-use SKILL.md:25
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    **API Key**: Read from environment variable `$CT_MONITOR_API_KEY` (all curl commands use `-H "Authorization: Bearer $CT_MONITOR_API_KEY"`)
    quoted
  • low Exfiltration net-credential-use SKILL.md:763
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    > - Format: "$TOKEN: Smart Money inflow $X + Y KOL mentions = 🔥 Double confirmed"
    quoted

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 16943 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 10Execution cost. Instruction body is 16943 tokens: crowds the task out of the window
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (ct-monitor) differs from the folder (openclaw-twitter-monitor)
  • 100Steps. 18 steps
  • 100Failures and branches. 21 branches, has a failure section
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -2125 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 315: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (60 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: clean
This is a disclosed crypto market monitoring skill with optional watchlist changes and scheduled Telegram reports that users should enable deliberately.
LLM: benign (high) · VirusTotal: · 29 May 2026